Automatically obtaining precision three dimensional information relative to a surface or object is vital to many industries and processes. For example, in the electronics assembly industry, precision three-dimensional information relative to an electrical component on a circuit board can be used to determine whether the component is placed properly. Further, three-dimensional information is also useful in the inspection of solder paste deposits on a circuit board prior to component mounting in order to ensure that a proper amount of solder paste is deposited in the proper location on the circuit board. Further still, three-dimensional information is also useful in the inspection of semiconductor wafers and flat panel display. Finally, as the precision of such three-dimensional information improves, it is becoming useful for a variety of additional industries and applications. However, as the precision of the three-dimensional information acquisition improves, it becomes more and more important to compensate for the various causes of minor system disturbances. Calibration of systems for obtaining three-dimensional is thus becoming increasingly important.
The calibration process for a three-dimensional structured light measurement sensor should compensate the projectors and cameras for the usual optical non-idealities, including lens geometric distortion, obliquity/keystone effects, rotation errors, and line of sight errors. Some of these non-idealities will not change appreciably over time to affect the measurement accuracy. However, following a sensor calibration, other non-idealities may drift appreciably over the time period of minutes to days and will affect measurement performance For example, line of sight may change appreciably due to thermal expansion from environmental changes.
Sophisticated, methods exist to accurately calibrate three-dimensional sensors and typically require precision equipment such as motion systems and calibration artifacts. It is also relatively time-consuming to acquire the necessary images of calibration artifacts and analyze them.